# 检查数据
python train_emernerf.py \
    --config_file configs/default_config.yaml \
    --output_root out \
    --project emernerf \
    --run_name 016 \
    --render_data_video_only \
    data.scene_idx=16 \
    data.pixel_source.load_size=[160,240] \
    data.pixel_source.num_cams=3 \
    data.start_timestep=0 \
    data.end_timestep=-1

# 2024/1/23-24 没有eval，将整个数据集都当作训练集，看下最终的PSNR是什么，与给定真值pose做对比
# 原本的,没有划分数据集，带有真值pose, batch_size=4096, 而且没有dino feature
CUDA_VISIBLE_DEVICES=1 python train_emernerf.py \
   --enable_wandb \
   --project emernerf_poses_free \
   --config_file configs/default_flow.yaml \
   --output_root out \
   --run_name 016_vanilla_with_poses \
   data.scene_idx=16 \
   data.start_timestep=0 \
   data.end_timestep=-1 \
   data.pixel_source.num_cams=1 \
   data.pixel_source.test_image_stride=0 \
   logging.saveckpt_freq=25000 \
   optim.num_iters=25000
# learn pose
CUDA_VISIBLE_DEVICES=0 python train_emernerf.py \
   --enable_wandb \
   --project emernerf_poses_free \
   --config_file configs/default_flow.yaml \
   --output_root out \
   --run_name 016_pose_free_b2048 \
   data.scene_idx=16 \
   data.start_timestep=0 \
   data.end_timestep=-1 \
   data.pixel_source.num_cams=1 \
   data.pixel_source.test_image_stride=0 \
   logging.saveckpt_freq=50000 \
   optim.num_iters=50000
# train per image
CUDA_VISIBLE_DEVICES=0 python train_emernerf.py \
   --enable_wandb \
   --project emernerf_poses_free \
   --config_file configs/default_flow.yaml \
   --output_root out \
   --run_name 016_pose_free_b4096_per_image_fix \
   data.scene_idx=16 \
   data.start_timestep=0 \
   data.end_timestep=-1 \
   data.pixel_source.num_cams=1 \
   data.pixel_source.test_image_stride=0 \
   logging.saveckpt_freq=4000 \
   optim.num_iters=50000
# 使用per image的方式去训练原本的emer
CUDA_VISIBLE_DEVICES=1 python train_emernerf.py \
   --enable_wandb \
   --project emernerf_poses_free \
   --config_file configs/default_flow.yaml \
   --output_root out \
   --run_name 016_vanilla_with_poses_per_image \
   data.scene_idx=16 \
   data.start_timestep=0 \
   data.end_timestep=-1 \
   data.pixel_source.num_cams=1 \
   data.pixel_source.test_image_stride=0 \
   logging.saveckpt_freq=10000 \
   optim.num_iters=10000
# 使用all_image训练pose_free
CUDA_VISIBLE_DEVICES=0 python train_emernerf.py \
   --enable_wandb \
   --project emernerf_poses_free \
   --config_file configs/default_flow.yaml \
   --output_root out \
   --run_name 016_pose_free_b4096_all_image \
   data.scene_idx=16 \
   data.start_timestep=0 \
   data.end_timestep=-1 \
   data.pixel_source.num_cams=1 \
   data.pixel_source.test_image_stride=0 \
   logging.saveckpt_freq=4000 \
   optim.num_iters=50000

# 之前render整张图的时候使用的是真值pose，当使用预测pose的时候会是什么样子
CUDA_VISIBLE_DEVICES=0 python train_emernerf.py \
   --enable_wandb \
   --project emernerf_poses_free \
   --config_file configs/default_flow.yaml \
   --output_root out \
   --run_name 016_pose_free_b2048_per_image_fix_rendering \
   data.scene_idx=16 \
   data.start_timestep=0 \
   data.end_timestep=-1 \
   data.pixel_source.num_cams=1 \
   data.pixel_source.test_image_stride=0 \
   logging.saveckpt_freq=4000 \
   optim.num_iters=50000
